The provided code models cognitive processes related to spatial learning and memory in a virtual environment known as the HexWaterMaze, which is inspired by the Morris Water Maze used in biological research. This is a circular pool typically filled with opaque water, where rodents must learn to find a hidden platform using spatial cues. The computational model replicates this experiment to investigate the roles of different brain regions, particularly the hippocampus and dorsolateral striatum, in spatial memory and learning processes. ### Biological Basis 1. **Hippocampus (HPC):** - The code references lesions to the hippocampus through the parameter `lesion_hpc`, signifying a focus on the hippocampus's role in spatial navigation and memory encoding. - In biological terms, the hippocampus is crucial for forming and retrieving memories, particularly spatial memories, that allow organisms to navigate environments using cognitive maps. 2. **Dorsolateral Striatum (DLS):** - Similarly, the parameter `lesion_dls` indicates the study of the dorsolateral striatum's influence. The DLS is associated with habit formation and procedural learning, contributing to stimulus-response forms of navigation. - The interplay between the hippocampus and striatum is of interest in understanding how different types of learning strategies (cognitive map-based vs. stimulus-response) are represented in the brain. 3. **Lesion Studies:** - The model simulates lesions to these brain regions to examine their contributions to task performance, modeling either a single lesion (`dls` or `hpc`) or dual lesions (`double`), as well as a control group equivalent (`sham`). - This mirrors experimental lesion studies in animals, which help elucidate the functional specialization of brain areas by observing behavioral deficits or changes following targeted brain damage. 4. **Memory and Learning Processes:** - The alternating platform locations in the model mimic changes in environmental context, testing the agents' ability to adapt to new conditions and highlighting processes of memory consolidation and retrieval. - The `agent` characterized by learning parameters such as `inv_temp`, `gamma`, and `learning_rate`, simulates reinforcement learning thought to be akin to neural processes that underpin learning and decision-making. 5. **Probe Trials:** - The implementation of probe trials, where the platform location is changed, examines the flexibility and robustness of the learned spatial strategies without direct reinforcements. This is a common method in biological experiments to assess the strength of spatial memory. In summary, this computational model articulates a focused investigation on spatial learning and memory mechanisms by simulating water maze navigation, with an emphasis on understanding hippocampus and striatum contributions. These simulations aspire to reflect the intricately coordinated neural dynamics observed in vertebrate models, providing insights into cognitive processes tied to navigation and memory.